Determinants of house prices in Lebanon: an ARDL approach

Abstract

Purpose: The purpose of this thesis is to investigate the variables affecting house prices in Lebanon in the long run and the short run. Design/ Methodology/ Approach: To answer the above question, data collected is a monthly one covering second half of the year 2013 until February 2021. The dependent variable is average housing price, while independent variables include employment index, construction permits, non-resident deposits, interest rate, CPI, and coincident indicators. The autoregressive distributed lag (ARDL) model is applied for the long run and the error correction model (ECM) is applied for the short run. Findings: The results show that, in the long run, the employment index (EI), which is a proxy of employment, affected house prices. In the short run, EI, construction permits, and interest on USD loans (USD) affected house prices in Lebanon. Research Limitations and Implications: There are various limitations concerning the thesis. First, average house prices do not necessarily represent housing since real estate is both residential and commercial. Second, average house prices differ from median house prices which are a more fair representation of housing whose data is not available. Third, there are no large datasets in Lebanon and data used in the thesis was limited to being less than 100 observations. There are also several implications. Findings will help policymakers determine which variables affect housing and how they could structure their policies based on the information. Real estate develepors will know when to build housing units and how to build and price them. It can also help the average house buyer determine the right time to buy a house.